diff --git a/src/config/settings.py b/src/config/settings.py
index d01dd1b..d12abe1 100644
--- a/src/config/settings.py
+++ b/src/config/settings.py
@@ -55,17 +55,13 @@ class Settings(BaseSettings):
     max_price: float = Field(default=0.90, alias="MAX_PRICE")
 
     # Monitoring Settings
-    fetch_interval_seconds: int = Field(default=15, alias="FETCH_INTERVAL_SECONDS")
     trending_markets_limit: int = Field(default=50, alias="TRENDING_MARKETS_LIMIT")
 
-    # Tiered market monitoring (full-coverage mode)
+    # Market coverage (volume thresholds for monitoring list)
     full_market_scan: bool = Field(default=True, alias="FULL_MARKET_SCAN")
     tier1_volume_min: float = Field(default=500_000, alias="TIER1_VOLUME_MIN")
     tier2_volume_min: float = Field(default=10_000, alias="TIER2_VOLUME_MIN")
     tier3_volume_min: float = Field(default=1_000, alias="TIER3_VOLUME_MIN")
-    tier1_poll_interval: int = Field(default=15, alias="TIER1_POLL_INTERVAL")
-    tier2_poll_interval: int = Field(default=60, alias="TIER2_POLL_INTERVAL")
-    tier3_poll_interval: int = Field(default=300, alias="TIER3_POLL_INTERVAL")
 
     # LLM Settings
     llm_model: str = Field(default="gemini-3.1-pro-preview", alias="LLM_MODEL")
diff --git a/src/services/trade_monitor.py b/src/services/trade_monitor.py
index f7d456a..c9c85c7 100644
--- a/src/services/trade_monitor.py
+++ b/src/services/trade_monitor.py
@@ -229,6 +229,7 @@ class TradeMonitor:
         3. Resolution window — like DTE filter (3-60 days sweet spot)
         4. Size — like premium filter ($250K+ minimum)
         5. Dynamic size — like dynamic_premium (base × √(vol / baseline))
+        5.5 Normalized size — like normalized_premium (usdc / √(vol))
         6. Signal strength — like ask_ratio filter (conviction check)
         """
         # --- 1. Price range ---
@@ -268,6 +269,16 @@ class TradeMonitor:
         if activity.usdc_size < threshold:
             return False
 
+        # --- 5.5 Normalized size (like normalized_premium) ---
+        # usdc_size / √(volume) makes signals comparable across market sizes.
+        # A $5K trade in a $50K market is far more significant than $20K in a $10M market.
+        if market and market.volume > 0:
+            normalized = activity.usdc_size / math.sqrt(market.volume)
+            # Minimum normalized threshold: filters out trades that are trivial
+            # relative to market size (calibrated: $5K in a $1M market → 5.0)
+            if normalized < 1.5:
+                return False
+
         # --- 6. Signal strength ---
         if market and market.outcome_prices:
             if activity.outcome == "Yes":